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research article

Uncertainty Feature Optimization: an implicit paradigm for problems with noisy data

Eggenberg, Niklaus
•
Salani, Matteo  
•
Bierlaire, Michel  
2011
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Optimization problems with noisy data solved using stochastic programming or robust optimization approaches require the explicit characterization of an uncertainty set U that models the nature of the noise. Such approaches depend on the modeling of the uncertainty set and suffer from an erroneous estimation of the noise.

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